Use of post-graduate students' research in evidence informed health policies: a case study of Makerere University College of Health Sciences, Uganda
Bibliographic record
Abstract
BACKGROUND: World over, stakeholders are increasingly concerned about making research useful in public policy-making. However, there are hardly any reports linking production of research by students at institutions of higher learning to its application in society. We assessed whether and how post-graduate students' research was used in evidence-informed health policies. METHODS: This is a multiple case study of master's students' dissertations at Makerere University College of Health Sciences (MakCHS) produced between 1996 and 2010. In a structured review, we applied a theoretical framework of 'research use' and used content analysis to map how research was used in public policy documents. We categorised content of these documents according to the health-related Millennium Development Goals (MDG). We defined a case of 'use' as citation of research products from a master's student's dissertation in a public policy-related document. RESULTS: We found 22 cases of research use in policy-related documents (0.5%) out of a total 4230 citations from 16 of 1172 total dissertations (1.4%). Additionally, research was mostly cited in primary studies (95.4%), systematic reviews (3%), narrative reviews (0.8%) and cost-effectiveness analyses (0.2%). Research was predominantly used instrumentally, to either frame the problem (burden of disease or health condition) or select an intervention (treatment or diagnostic option) and rarely symbolically to justify strategies already selected. The bulk of the cases of research use addressed child health (MDG 4), focusing on infectious diseases (MDG 6), mainly in international clinical or public health guidelines, working papers, a consensus statement and a global report. We distilled 'synergistic relationships' among organisations or interest groups, 'globalisation of local evidence', 'trade-offs' in the use of research and use of 'negative results' from the documents and text content. CONCLUSIONS: Research from dissertations of post-graduate students at MakCHS is used in evidence-informed health policies, particularly for infectious diseases in child health. Further, we have delineated pathways of research use in the global arena and highlighted the importance of 'negative results' from dissertations of post-graduate students at MakCHS.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
| gpt | Scholarly communication Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Qualitative | medium |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.116 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".